Parameter estimation for the stochastic SIS epidemic model

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In this paper we estimate the parameters in the stochastic SIS epidemic model by using pseudo-maximum likelihood estimation (pseudo-MLE) and least squares estimation. We obtain the point estimators and 100(1 − α)% confidence intervals as well as 100(1 − α)% joint confidence regions by applying least squares techniques. The pseudo-MLEs have almost the same form as the least squares case. We also obtain the exact as well as the asymptotic 100(1 − α)% joint confidence regions for the pseudo-MLEs. Computer simulations are performed to illustrate our theory.
Original languageEnglish
Pages (from-to)75-98
Number of pages24
JournalStatistical Inference for Stochastic Processes
Issue number1
Publication statusPublished - 1 Apr 2014


  • Stochastic SIS epidemic model
  • pseudo-maximum likelihood estimation
  • least squares estimation
  • confidence interval
  • confidence region
  • asymptotic estimator
  • logistic equations

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